3 papers
cs.LG2026
From Snapshots to Trajectories: Learning Single-Cell Gene Expression Dynamics via Conditional Flow Matching
Siyu Pu, Qingqing Long, Xiaohan Huang +7
Single-cell RNA sequencing (scRNA-seq) provides high-dimensional profiles of cellular states, enabling data-driven modeling of cellular dynamics over time. In practice, time-resolv…
q-bio.GN2025
scCluBench: Comprehensive Benchmarking of Clustering Algorithms for Single-Cell RNA Sequencing
Ping Xu, Zaitian Wang, Zhirui Wang +5
Cell clustering is crucial for uncovering cellular heterogeneity in single-cell RNA sequencing (scRNA-seq) data by identifying cell types and marker genes. Despite its importance,…
q-bio.GN2025
scUnified: An AI-Ready Standardized Resource for Single-Cell RNA Sequencing Analysis
Ping Xu, Zaitian Wang, Zhirui Wang +7
Single-cell RNA sequencing (scRNA-seq) technology enables systematic delineation of cellular states and interactions, providing crucial insights into cellular heterogeneity. Buildi…